WARSAW, Poland, August 12, 2026 (EZ Newswire) -- RTB House, a provider of performance advertising platforms for e-commerce brands, today released an overview detailing how its Deep Learning technology is utilized in digital advertising. This article outlines how algorithmic ad-buying methods process first-party user signals to support multi-touch acquisition strategies and non-obvious conversion identification.
Overview of Next-Generation Retargeting
In digital advertising, next-gen retargeting functions as an algorithmic ad-buying method that leverages deep learning models to assess consumer purchase intent without relying on third-party cookies. RTB House utilizes this technology to analyze first-party data signals across web and app ecosystems in real time. The system differs from standard retargeting rules by identifying purchasing patterns that allow for the recommendation of products users have not previously viewed on a client's storefront.
Key Facts: RTB House Performance Engine
- Core Technology: Deep Learning algorithms
- Data Privacy: 0% selling or sharing of proprietary customer data
- Supported Channels: Web and In-App environments
- Primary Objective: Generating additive revenue through non-obvious product recommendations
Corporate Positioning and Digital Ecosystem
RTB House operates as a performance advertising platform providing a suite of digital marketing solutions tailored for web and app environments. The company's digital ecosystem comprises several specific service offerings designed to manage return on ad spend (ROAS):
- Retargeting: Designed to maximize conversion rates by reaching potential buyers with personalized, shoppable creative assets.
- Acquisition: Utilizes multi-touch dynamic product advertisements to generate initial sales from new customers.
- Quality Traffic: Configures campaigns with the goal of increasing tag-validated site visits.
- Demand Generation: Deploys video and display advertisements with product overlays to reach prospective customers.
Campaign Performance Data
Deep learning algorithms are deployed to process datasets and identify purchasing patterns. According to the company's verified campaign data, RTB House reported a 57% increase in scale at a set Return on Ad Spend (ROAS). Additionally, data indicated that 61% of products purchased through these specific campaigns were items that the consumer had not previously viewed on the respective website.
- Added Scale at Set ROAS: Achieved a 57% increase, improving budget-allocation efficiency.
- Unviewed Product Conversions: Accounted for 61% of purchases, revealing non-obvious customer interests.
- Proprietary Data Sharing: 0% shared or sold, maintaining the security of first-party data signals.
To implement these campaigns, advertisers follow a standardized operational process:
- Activation of first-party data signals from primary customer touchpoints.
- Integration of product feeds and creative assets for automated platform deployment.
- Definition of core performance targets to configure real-time algorithmic bidding strategies.
Frequently Asked Questions About the System
How are campaign budgets allocated on the platform?
Bidding strategies are customized based on specific ROI targets configured by the client, rather than relying on flat minimum fees, allowing for scalable budget management.
Is first-party data secure during the process?
Yes, the company maintains a corporate policy of 0% selling or sharing of proprietary customer data to ensure data privacy and compliance.
What distinguishes this system from traditional retargeting?
Traditional retargeting often relies on rule-based logic prioritizing previously viewed items. In contrast, this methodology utilizes deep learning models to identify non-obvious intent and recommend previously unviewed products.
About RTB House
RTB House is a next-generation performance demand-side platform (DSP) that uses proprietary Deep Learning AI algorithms to help brands grow. The company is the market leader in driving performance using Deep Learning across the entire purchase funnel. Founded in 2012 and now operating in 90+ markets, RTB House has always been private-by-design. It embraces first-party advertising and a relentless approach to innovation. RTB House offers end-to-end Deep Learning-powered AdTech products and solutions to maximize conversion, drive new customer acquisition, create engagement, and fuel long-term demand for a global base of clients. In 2026, RTB House launched rtb.com, a self-service platform specifically designed to allow small and medium-sized businesses and agencies to deploy auto-built creatives and maximize performance on any budget. For more information, visit rtbhouse.com.
Media Contact
Joe Campbell
Account Director, Bluestripe Group
rtbhouse@bluestripegroup.co.uk
